Traces of Social Competence in Large Language Models
arXiv:2603.04161v1 Announce Type: new Abstract: The False Belief Test (FBT) has been the main method for assessing Theory of Mind (ToM) and related socio-cognitive competencies....
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arXiv:2603.04161v1 Announce Type: new Abstract: The False Belief Test (FBT) has been the main method for assessing Theory of Mind (ToM) and related socio-cognitive competencies....
arXiv:2603.04162v1 Announce Type: new Abstract: We present Bielik-Q2-Sharp, the first systematic academic evaluation of extreme 2-bit quantization applied to a Polish large language model. Using...
arXiv:2603.04163v1 Announce Type: new Abstract: Wildlife re-identification aims to recognise individual animals by matching query images to a database of previously identified individuals, based on...
arXiv:2603.04165v1 Announce Type: new Abstract: Large-scale 2D foundation models exhibit strong transferable representations, yet extending them to 3D volumetric data typically requires retraining, adapters, or...
arXiv:2603.04166v1 Announce Type: new Abstract: Developing exoskeleton controllers that generalize across diverse locomotor conditions typically requires extensive motion-capture data and biomechanical labeling, limiting scalability beyond...
arXiv:2603.04168v1 Announce Type: new Abstract: The increasingly complex Web3 ecosystem and decentralized finance (DeFi) landscape demand ever higher levels of technical expertise and financial literacy...
arXiv:2603.04169v1 Announce Type: new Abstract: Query rewriting is essential for database performance optimization, but existing automated rule enumeration methods suffer from exponential search spaces, severe...
arXiv:2603.04176v1 Announce Type: new Abstract: Context graphs are essential for modern AI applications including question answering, pattern discovery, and data analysis. Building accurate context graphs...
arXiv:2603.04177v1 Announce Type: new Abstract: Large language model (LLM) coding agents can generate working code, but their solutions often accumulate complexity, duplication, and architectural debt....
arXiv:2603.04179v1 Announce Type: new Abstract: We present NOVA3R, an effective approach for non-pixel-aligned 3D reconstruction from a set of unposed images in a feed-forward manner....
arXiv:2603.04180v1 Announce Type: new Abstract: We introduce the Probability Navigation Architecture (PNA) framework, which treats neural computation as navigation through a probability manifold governed by...
arXiv:2603.04181v1 Announce Type: new Abstract: Harmful algal blooms (HABs) can threaten coastal infrastructure, fisheries, and desalination dependent water supplies. This project (REDNET-ML) develops a reproducible...
arXiv:2603.04186v1 Announce Type: new Abstract: Log data are essential for intrusion detection and forensic investigations. However, manual log analysis is tedious due to high data...
arXiv:2603.04189v1 Announce Type: new Abstract: This work presents a general framework for the operationally driven optimal siting and sizing of battery energy storage systems in...
arXiv:2603.04191v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly serving as personal assistants, where users share complex and diverse preferences over extended interactions....
arXiv:2603.04194v1 Announce Type: new Abstract: Training large-scale Neural Networks requires substantial computational power and energy. Federated Learning enables distributed model training across geospatially distributed data...
arXiv:2603.04203v1 Announce Type: new Abstract: Substation reconfiguration via busbar splitting can mitigate transmission grid congestion and reduce operational costs. However, existing approaches neglect the security...
arXiv:2603.04205v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) achieve near-perfect scores on digital document benchmarks like OmniDocBench, their performance in the unpredictable physical world...
arXiv:2603.04208v1 Announce Type: new Abstract: Ground segmentation in point cloud data is the process of separating ground points from non-ground points. This task is fundamental...
arXiv:2603.04209v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are increasingly adopted across domains such as molecular biology and social network analysis, yet their black-box...
arXiv:2603.04212v1 Announce Type: new Abstract: The rapid adoption of Large Language Models (LLMs) has transformed modern software development by enabling automated code generation at scale....
arXiv:2603.04216v1 Announce Type: new Abstract: We develop a statistically robust framework for reconstructing metal--semiconductor contact regions using topological gradients. The inverse problem is formulated as...
arXiv:2603.04217v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly mediate global information access with the potential to shape public discourse, their alignment with...
arXiv:2603.04219v1 Announce Type: new Abstract: We investigate the use of zero-shot text-to-speech (ZS-TTS) as a data augmentation source for low-resource personalized speech synthesis. While synthetic...